FT-IR-based fingerprint combined with unsupervised chemometric analysis revealed particle sizes and aqueous-ethanol ratio alter the chemical composition and nutraceutical value of Daucus carota.

This study reported the effects of particle size of dry powder and the optimum solvent extraction on the nutraceutical value of carrot by observing its FT-IR fingerprint, TPC, TFC, and antioxidant activity. The dried-powdered carrot was ultrasound-assisted extracted using EtOH, water, and EtOH-water. The TFC, TPC, and antioxidant activity were analysed by a colorimetric method using a spectrophotometry UV-Vis. The chemotaxonomy of samples was analysed using FT-IR combined with chemometrics analysis. The TFC, TPC, and antioxidant capacity were significantly different for each sample with the highest TFC, TPC, and antioxidant obtained on particle size 149 µm with EtOH-water (50:50) as the most prominent solvent (19.51 mgQE/g, 9.90 mgGAE/g, IC50: 16.7 ± 0.89 µg/mL). FT-IR profiling of samples also illustrates a minor different pattern of the spectrum, indicating there is a difference in their chemical composition. The particle size and EtOH-water ratio influence the chemical composition and antioxidant activity of carrots.

Chemical constituent characterization and determination of Quisqualis fructus based on UPLC-Q-TOF-MS and HPLC combined with fingerprint and chemometric analysis.

Quisqualis fructus (QF) is a traditional Chinese medicine (TCM) that it has a long history in the therapeutic field of killing parasites, eliminating accumulation, and stopping diarrhea. However, the therapeutic material basis of QF is remaining ambiguous nowadays. The geographical origin differences of QF are also usually ignored in the process of medication. In this study, the alcohol-aqueous soluble constituents in QF from different origins were systematically characterized and accurately measured by ultra-high performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and high-performance liquid chromatography (HPLC) respectively. Chemometric analysis was performed for origin differentiation and screening of potential quality marker (Q-marker). Finally, A total of 106 constituents were tentatively characterized in positive and negative ion modes, including 29 fatty acids, 26 organic acids, 11 amino acids and derivatives, 10 glycosides, 9 alkaloids and derivatives, and 21 other constituents. QF from different origins were effectively distinguished and 16 constituents were selected as the potential Q-markers subsequently. Four representative components (trigonelline, adenosine, ellagic acid, and 3,3'-di-O-methylellagic acid) in QF samples were simultaneously determined. HPLC fingerprint analysis indicated that the similarity between 16 batches of QF was in the range of 0.870-0.999. The above results provide some insights for the research on the pharmacodynamic constituents, quality control, and geographical discrimination of QF.

Enhancing sub-catchment sediment source fingerprinting using chemometric models for DRIFTS in different particle size subfractions.

Understanding the origins of sediment within stream networks is critical to developing effective strategies to mitigate sediment delivery and soil erosion in larger drainage basins. Sediment fingerprinting is a widely accepted approach to identifying sediment sources; however, it typically relies on labor-intensive and costly chemical analyses. Recent studies have recognized diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) as a non-destructive, cost-effective, and efficient alternative for estimating sediment contributions from multiple sources. This study aimed to assess (i) the effects of different particle size fractions on DRIFTS and conservatism tests, (ii) the effects of spectral pre-processing on discriminating sub-catchment spatial sediment sources, (iii) the efficiency of partial least squares regression (PLSR) and support vector machine regression (SVMR) chemometric models across different spectral resolutions and particle size fractions, and (iv) the quantification of sub-catchment spatial sediment source contributions using chemometric models across different particle size fractions. DRIFTS analysis was performed on three particle size fractions (<38 µm, 38-63 µm, and 63-125 µm) using 54 sediment samples from three different sub-catchments and 26 target sediment samples from the Andajrood catchment in Iran. Results showed significant effects of particle size fractions on DRIFTS for both sub-catchment sediment sources and target sediment samples. Conservatism tests indicated that DRIFTS behave conservative for the majority of target sediment samples. Spectral pre-processing techniques including SNV + SGD1 and SGD1 effectively discriminated sources across all particle size fractions and spectral resolutions. However, the optimal combination of pre-processing, spectral resolution, and regression models varied between sub-fractions. Validated model estimates revealed that sub-catchment 1 consistently contributed the most sediment across all particle size fractions, followed by sub-catchments 3 and 2. These results highlight the effectiveness of DRIFTS as a rapid, cost-effective, and precise method for discriminating and apportioning sediment sources within spatial sub-catchments.

Calotropis procera and the Pharmacological Properties of Its Aqueous Leaf Extract: A Review.

Calotropis procera (C. procera) is a versatile plant often used for fuel, fodder, wood, fiber, phytoremediation, medicine, and synthesis of nanoparticles. Its ability to tolerate abiotic stresses and its morphophysiological adaptation have made it popular worldwide. Currently, it is identified as an environmental weed across the world. C. procera owes its therapeutic qualities to the secondary metabolites like tannins, alkaloids, and phenols present in it. New synthetic drugs are being formulated by using these secondary metabolites as a prototype. This review aimed to provide a summary of the chemometric profile, toxicity, and pharmacological activities of the aqueous leaf extract of C. procera based on the current literature.

An Optimized Microwave-Assisted Digestion Method to Analyze the Amino Acids Profile of Quisqualis Fructus from Different Planted Origins.

This study aims to establish a rapid and convenient microwave-assisted digestion method for sample pretreatment to determine amino acid profiles in natural products. This method was applied to analyze the amino acid profiles of Quisqualis Fructus (QF) from different planted origins. The microwave-assisted digestion conditions were optimized by a response surface methodology (RSM), and 17 amino acids in different planted origins of QF were determined by an automatic amino acid analyzer according to the optimized digestion conditions. The contents of 17 amino acids in QF from different planted origins were further analyzed by fingerprint and chemometric analysis. The temperature of microwave digestion at 167 °C, time of microwave digestion at 24 min, and a solid-liquid ratio of 46.5 g/mL was selected as the optimal digestion conditions. The total content of 17 amino acids in QF from different planted origins ranged from 71.88 to 91.03 mg/g. Amino acid composition and nutritional evaluation indicated that the content of medicinal amino acids was higher than aromatic amino acids. The results of fingerprint analysis reflected that the similarity between the 16 batches of QF ranged from 0.889 to 0.999, while chemometrics analysis indicated amino acid content in QF varied from different planted origins, and six important differential amino acids were screened. Compared with the traditional extraction method, microwave-assisted digestion with response surface optimized has the advantages of rapidity, convenience, and reliability, which could be used to study the amino acid profiles in natural products. The amino acid profile of QF indicated that it has a rich medicinal nutritional value. Different planted origins of QF have a high degree of similarity and could be effectively distinguished by chemometric analysis.

Regression Models for In Vivo Discrimination of the Iberian Pig Feeding Regime after Near Infrared Spectroscopy Analysis of Faeces.

The Iberian pig is a native breed of the Iberian Peninsula, which holds an international reputation due to the superior quality and the added value of its products. Different rearing practices and feeding regimes are regulated, resulting in different labelling schemes. However, there is no official analytical methodology that is standardised for certification purposes in the sector. Near Infrared Spectroscopy (NIRS) is a technology that provides information about the physicochemical composition of a sample, with several advantages that have enabled its implementation in different fields. Although it has already been successfully used for the analysis of Iberian pig's final products, samples evaluated with NIRS technology are characterised by a postmortem collection. The goal of this study was to evaluate the potential of NIRS analysis of faeces for in vivo discrimination of the Iberian pig feeding regime, using the spectral information per se for the development of modified partial least squares regressions. Faecal samples were used due to their easy collection, especially in extensive systems where pig handling is difficult. A total of 166 individual samples were collected from 12 farms, where the three different feeding regimes available in the sector were ensured. Although slight differences were detected depending on the chemometric approach, the best models obtained a classification success and a prediction accuracy of over 94% for feeding regime discrimination. The results are considered very satisfactory and suggest NIRS analysis of faeces as a promising approach for the in vivo discrimination of the Iberian pigs' diet, and its implementation during field inspections, a significative achievement for the sector.

Traceability Research on Geographic Erigeron breviscapus Based on High-Resolution Mass Spectrometry and Chemometric Analysis.

A method was developed to identify and trace the geographic sources of Erigeron breviscapus using high-resolution mass spectrometry and chemometrics. The representative samples were collected from the geographic area of Honghe Dengzhanhua and other areas in Yunnan province and Guizhou province. The data points could be determined well using the PCA and PLS-DA diagram. A total of 46 characteristic compounds were identified from Honghe Dengzhanhua and within Guizhou province, but 37 compounds were different from Honghe Dengzhanhua and other counties in Yunnan province. Two biomarkers were found from three regions. Their structures were inferred as 8-amino-7-oxononanoic acid and 8-hydroxyquinoline, and they had the same molecular composition. This may suggest that a possible synthesis pathway can be proven in the future.

The efficiency of Raphia hookeri adsorbent in indigo carmine dye removal: Economy depth via chemometrics.

The remediation of dye pollutants remains a concern in contemporary water management practices. Hence, the need for efficient and cost-effective techniques for dye removal from wastewater. In this study, the epicarp of Raphia hookeri fruits was treated with orthophosphoric acid for enhanced porosity and efficiency in the uptake of Indigo carmine dye (ICD). Treated Raphia hookeri fruit waste (RHPW) presented morphologically distributed pores as well as high porosity with Branneur-Emmet-Teller (BET) surface area of 945.43 m2/g. RHPW displayed functional groups suitable for adsorption. The maximum ICD uptake was observed at pH 5 while the maximum uptake (qmax) was 20.41 mg/g in the concentration range of 2-10 mg/L. Freundlich isotherm and Pseudo-second order kinetics well-described equilibrium and kinetics data respectively. This indicated a multilayered adsorption. The Dubinin-Radushkecich model energy value was 40.82 kJ/mol, indicating chemical adsorption. The ridge regression, the Lasso and the Elastic net statistical models were used to establish a positive relationship between the various adsorption operational parameters studied. Lasso provided the best result based on the estimated mean squared error. The RHPW-ICD adsorption system was more favorable at room temperature, as the removal efficiency decreased with temperature rise. The findings established Raphia hookeri fruit epicarp as an economical and sustainable precursor for the preparation of potent adsorbent for Indigo carmine dye removal. This can find possible application in wastewater treatment.

Quantification of antibiotics in food by octahedral gold-silver nanocages-based SERS sensor coupling multivariate calibration.

The abuse of antibiotics has caused gradually increases drug-resistant bacterial strains that pose health risks. Herein, a sensitive SERS sensor coupled multivariate calibration was proposed for quantification of antibiotics in milk. Initially, octahedral gold-silver nanocages (Au@Ag MCs) were synthesized by Cu2O template etching method as SERS substrates, which enhanced the plasmonic effect through sharp edges and hollow nanostructures. Afterwards, five chemometric algorithms, like partial least square (PLS), uninformative variable elimination-PLS (UVE-PLS), competitive adaptive reweighted sampling-PLS (CARS-PLS), random frog-PLS (RF-PLS), and convolutional neural network (CNN) were applied for TTC and CAP. RF-PLS performed optimally for TTC and CAP (Rc = 0.9686, Rp = 0.9648, RPD = 3.79 for TTC and Rc = 0.9893, Rp = 0.9878, RPD = 5.88 for CAP). Furthermore, the detection limit of 0.0001 µg/mL for both TTC and CAP was obtained. Finally, satisfactory (p > 0.05) results were obtained with the standard HPLC method. Therefore, SERS combined RF-PLS could be applied for fast, nondestructive sensing of TTC and CAP in milk.

Rapid non-destructive monitoring and quality assessment of the fumigation process of Shanxi aged vinegar based on Vis-NIR hyperspectral imaging combined with multiple chemometric algorithms.

The quality of the grains during the fumigation process can significantly affect the flavour and nutritional value of Shanxi aged vinegar (SAV). Hyperspectral imaging (HSI) was used to monitor the extent of fumigated grains, and it was combined with chemometrics to quantitatively predict three key physicochemical constituents: moisture content (MC), total acid (TA) and amino acid nitrogen (AAN). The noise reduction effects of five spectral preprocessing methods were compared, followed by the screening of optimal wavelengths using competitive adaptive reweighted sampling. Support vector machine classification was employed to establish a model for discriminating fumigated grains, and the best recognition accuracy reached 100%. Furthermore, the results of partial least squares regression slightly outperformed support vector machine regression, with correlation coefficient for prediction (Rp) of 0.9697, 0.9716, and 0.9098 for MC, TA, and AAN, respectively. The study demonstrates that HSI can be employed for rapid non-destructive monitoring and quality assessment of the fumigation process in SAV.

Non-linear responses via agglomeration and aggregation of gold nanoparticles for surface-enhanced Raman spectroscopy (SERS) coupled with chemometric analysis for chlorpyrifos detection.

This study investigates the behaviour of gold nanoparticles (AuNPs) when exposed to chlorpyrifos, an agricultural pesticide, and its application in detecting the pesticide via surface-enhanced Raman spectroscopy (SERS). Under synergistic addition of NaCl, AuNPs undergo agglomeration at lower chlorpyrifos concentrations but aggregation at higher concentrations, resulting in a distinctive nonlinear SERS response. A linear relationship is obtained between 0.001 and 1 ppm with detection limit (LOD) of 0.009 ppm, while an inverse response is observed at higher concentrations (1-1000 ppm) with a LOD of 1 ppm. Combining the colorimetric response of AuNP solutions, their absorbance spectra, and principal component analysis can improve detection reliability. The assay, coupled with a simple recovery method using acetonitrile swabbing, achieves high reproducibility in detecting chlorpyrifos in cucumber, even at concentrations as low as 0.11 ppm. This approach can be tailored for various chlorpyrifos concentrations not only in cucumbers but also in different food matrices.

Consumer insights into the at-home liking of commercial beers: Integrating nonvolatile and volatile flavor chemometrics.

Consumer acceptability of beers is influenced by product formulation and processing conditions, which impart unique sensory profiles. This study used multivariate techniques to evaluate at-home consumer sensory acceptability of six commercial beers considering their style, fermentation type, and chemical composition. Samples included top-fermented beers (American India Pale Ale and Stout) and bottom-fermented beers (Pilsner, zero-alcohol Pilsner, Vienna Lager, and Munich Dunkel). Beer consumers (n = 50) conducted sensory hedonic, check-all-that-apply (CATA) and just-about-right (JAR) tests. Chemometric variables included iso-alpha-acids, hordenine, and volatile aromatic compounds, quantified by chromatographic methods, whereas bitterness units (IBU) were determined spectrophotometrically. Lager beers had higher acceptability than top-fermented beer (p < .05) for all attributes. Light-colored beers and medium-height foams had the highest liking scores for visual sensory attributes. Higher concentrations of bitter-tasting molecules, hordenine, and acidity decreased the liking scores of top-fermented (Ale) beers, as a sensory penalty analysis suggested. In contrast, the most favored beers (Pilsners and Munich Dunkel) contained higher fusel alcohol esters linked to fruity aromatic notes. Although a low conversion rate of fatty acids into fruity esters was noted in nonalcoholic Pilsner, its overall liking score was not statistically different from the alcoholic version. However, consumers perceived the nonalcoholic Pilsner as less bitter than its alcoholic counterpart even when IBUs were nonsignificantly different. This study emphasized the significance of understanding beer chemometrics to comprehend consumer acceptability, highlighting the crucial role of bitter molecules. Hence, hordenine, acidity, and volatile contents provided additional and valuable insights into consumer preferences.

Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar.

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.

Rapid and sensitive approaches for detecting food fraud: A review on prospects and challenges.

Precise and reliable analytical techniques are required to guarantee food quality in light of the expanding concerns regarding food safety and quality. Because traditional procedures are expensive and time-consuming, quick food control techniques are required to ensure product quality. Various analytical techniques are used to identify and detect food fraud, including spectroscopy, chromatography, DNA barcoding, and inotrope ratio mass spectrometry (IRMS). Due to its quick findings, simplicity of use, high throughput, affordability, and non-destructive evaluations of numerous food matrices, NI spectroscopy and hyperspectral imaging are financially preferred in the food business. The applicability of this technology has increased with the development of chemometric techniques and near-infrared spectroscopy-based instruments. The current research also discusses the use of several multivariate analytical techniques in identifying food fraud, such as principal component analysis, partial least squares, cluster analysis, multivariate curve resolutions, and artificial intelligence.

Geochemical evaluation and the mechanism controlling groundwater chemistry using chemometric approach and groundwater pollution index (GPI) in the Kishangarh city of Rajasthan, India.

This study is primarily focused on delving into the geochemistry of groundwater in the Kishangarh area, located in the Ajmer district of Rajasthan, India. In pursuit of this research goal, the sampling locations were divided into three parts within the Kishangarh region: Badgaon Rural (KSGR), Kishangarh Urban (KSGU), and the Kishangarh RIICO marble industrial area (KSGI). Various analytical methods have been executed to assess the suitability of groundwater for various purposes based on pH, electric conductivity, total dissolved solids, hardness, salinity, major anions, and cations. The ionic trend of anions and cations was found as HCO3- > Cl- > SO42- > NO3- > Br- > NO2- > F- and Na+ > Ca2+ > Mg2+ > K+, respectively. Applying statistical techniques such as principal component analysis (PCA) and Pearson correlation matrix analysis (PCMA) makes it evident that the physicochemical attributes of water sourced from the aquifers in the study area result from a blend of diverse origins. In addition, Gibbs, Piper, Durov, and scatter plots were used to assess groundwater's geochemical evolution. Piper plot demonstrated the two types of groundwater facies, Na-HCO3- and Na-Cl, implying significant contributions from evaporitic dissolution and silicate weathering. Also, the scatter plots have evaluated the impression of mine acid leachate, evaporitic dissolution, and silicate weathering to upsurge salt formation in the groundwater. The pollution risk evaluation within the study area was conducted using the groundwater pollution index (GPI). This index revealed a prominent concern for pollution, particularly in the northern segment of the study region. As a result, it can be inferred that the fine aeolian sand and silt formations in the northern part are relatively more vulnerable to contamination.

Source-specific geochemical and health risk assessment of anthropogenically induced metals in a tropical urban waterway.

Thorough deliberation is necessary to safeguard the tropical urban streams near the shoreline from human interference, as it is becoming a notable environmental danger. Consequently, an in-depth study was carried out on a significant urban waterway located on the southern seashore of Bangladesh, which is positioned in the Bengal delta, renowned as the largest delta in the globe. The current investigation assesses the potential health hazards associated with trace metals (Hg, Cu, As, Pb, Ni, Zn, Cd, Cr, Fe, and Mn) and uses chemometric analysis to determine where they originate. Likewise geochemical methods are used to analyze the levels of trace metal enrichment and pollution in the sediments of the river. Almost all of the elements' mean concentrations were observed to be within the standard limits. The findings not only demonstrate the extent of trace metal contamination but also the health threats that it poses to the public (male, female, and children) by polluting the sediment. For all age groups of people, the hazard index was <1, suggesting there was no non-carcinogenic threat. Regardless of age and sex, exposure occurred in descending order: ingestion > dermal > inhalation. Total carcinogenic risk (TCR) values for males, females, and children were 1.45E-05, 1.56E-05, and 1.34E-04, respectively, recommending that children are at greater vulnerability than adults. The geochemical approach and chemometric analysis corroborate the human-induced impact of trace metal loading in the sediment of the waterway, which is predominantly caused by the oil industry, domestic garbage, and untreated waste discharge.

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques.

INTRODUCTION: Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools. OBJECTIVES: The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources. METHODS: The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar." RESULTS: An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds. CONCLUSION: Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Chemometric Analysis and Human Health Implications of Trace and Heavy/Non-Essential Metals through ingestion of Carbonated and Non-Carbonated Beverages.

Elevated levels of trace metals (TMs) and heavy/non-essential metals (HnMs) in commonly consumed beverages concern the public and regulatory agencies. Thus, frequent monitoring of these metals is critically important. The present study intended to assess TMs and HnMs concentrations and associated health risks in beverages. Ten metals, such as Mn, Co, Cr, Cu, and Zn (TMs) and Ni, Cd, Pb, Al, and As (HnMs), were quantified in different beverage brands categorized into two groups such as non-carbonated and carbonated beverages. Chemometric analysis such as hierarchical cluster analysis (HCA), Pearson's correlation coefficient (PCC), and principal component analysis (PCA) were also performed to demonstrate the possible natural and anthropogenic sources of metal contamination. Among the TMs, the mean concentration of Zn (233.3 ± 3.3-291.7 ± 3.2 µg/L) followed by Mn (119.0 ± 2.3-146.4 ± 2.2 µg/L) was found highest in both carbonated and non-carbonated beverage samples. In the case of HnMs, the lowest mean concentration of Cd (7.4 ± 0.9-18.6 ± 1.2 µg/L) followed by Pb (4.1 ± 0.4-4.5 ± 0.4 µg/L) was observed in both types of beverage samples. The tolerable dietary intake (TDI) value for Ni and provisional tolerable monthly intake (PTMI) value for Cd were higher than the value established by the WHO and EFSA. The computed values of the hazard index (HI < 1) and the cumulative cancer risk (CCR) indicated a low risk of exposure.

Metabolomics analysis based on UHPLC-QqQ-MS/MS to discriminate grapes and wines from different geographical origins and climatological characteristics.

With the proliferation of the consumer's awareness of wine provenance, wines with unique origin characteristics are increasingly in demand. This study aimed to investigate the influence of geographical origins and climatological characteristics on grapes and wines. A total of 94 anthocyanins and 78 non-anthocyanin phenolic compounds in grapes and wines from five Chinese viticultural vineyards (CJ, WH, QTX, WW, and XY) were identified by UHPLC-QqQ-MS/MS. Chemometric methods PCA and OPLS-DA were established to select candidate differential metabolites, including flavonols, stilbenes, hydroxycinnamic acids, peonidin derivatives, and malvidin derivatives. CCA showed that malvidin-3-O-glucoside had a positive correlation with mean temperature, and quercetin-3-O-glucoside had a negative correlation with precipitation. In addition, enrichment analysis elucidated that the metabolic diversity in different origins mainly occurred in flavonoid biosynthesis. This study would provide some new insights to understand the effect of geographical origins and climatological characteristics on phenolic compounds in grapes and wines.

Macromolecules with predominant ß-pleated sheet proteins in extracellular vesicles released from Raphanus sativus L. var. caudatus Alef microgreens induce DNA damage-mediated apoptosis in HCT116 colon cancer cells.

Plant-derived bioactive macromolecules (i.e., proteins, lipids, and nucleic acids) were prepared as extracellular vesicles (EVs). Plant-derived EVs are gaining pharmaceutical research interest because of their bioactive components and delivery properties. The spherical nanosized EVs derived from Raphanus sativus L. var. caudatus Alef microgreens previously showed antiproliferative activity in HCT116 colon cancer cells from macromolecular compositions (predominantly proteins). To understand the mechanism of action, the biological activity studies, i.e., antiproliferation, cellular biochemical changes, DNA conformational changes, DNA damage, apoptotic nuclear morphological changes, apoptosis induction, and apoptotic pathways, were determined by neutral red uptake assay, synchrotron radiation-based Fourier transform infrared microspectroscopy, circular dichroism spectroscopy, comet assay, 4',6-diamidino-2-phenylindole (DAPI) staining, flow cytometry, and caspase activity assay, respectively. EVs inhibited HCT116 cell growth in concentration- and time-dependent manners, with a half-maximal inhibitory concentration of 675.4 ± 33.8 µg/ml at 48 h and a selectivity index of 1.5 ± 0.076. HCT116 treated with EVs mainly changed the cellular biochemical compositions in the nucleic acids and carbohydrates region. The DNA damage caused no changes in DNA conformation. The apoptotic nuclear morphological changes were associated with the increased apoptotic cell population. The apoptotic cell death was induced by both extrinsic and intrinsic pathways. EVs have potential as antiproliferative bioparticles.